Various principles and methods are known in the field of electronic and electro-optical distance measurement. One approach consists in emitting pulsed electromagnetic radiation, such as e.g. laser light, onto a target to be measured and in receiving an echo from said target as a backscattering object, wherein the distance to the target to be measured can be determined for example on the basis of the time of flight, the shape, and/or the phase of the pulse. Such laser distance measuring devices have gained acceptance in the meantime as standard solutions in many fields.
Two different approaches or a combination thereof are usually used for detecting the backscattered pulse.
The so-called threshold value method involves detecting a light pulse if the intensity of the radiation incident on a detector of the distance measuring apparatus used exceeds a certain threshold value. Said threshold value prevents noise and interference signals from the background from being erroneously detected as a useful signal, i.e. as backscattered light of the emitted pulse. The other approach is based on the sampling of the backscattered pulse. This approach is typically used in the case of weak backscattered signals (e.g. pulse signals), such as are caused for example by relatively large measurement distances, or generally for increasing the measurement accuracy. An emitted signal is detected by virtue of the fact that the radiation detected by a detector is sampled, a signal is identified within the sampled region and, finally, a position of the signal is determined temporally. By using a multiplicity of samples and/or summation of the reception signal synchronously with the emission rate, it is possible to identify a useful signal even under unfavorable circumstances, such that it is possible to cope with even relatively large distances or background scenarios that are noisy or beset by disturbances.
Nowadays, the entire waveform of the analog signal of the radiation detected by a detector is often sampled here by means of the waveform digitizing (WFD) method. After identification of the coding of the associated transmission signal (ASK, FSK, PSK, etc.) of a received signal, a signal time of flight (“pulse time of flight”) is determined very accurately from a defined profile point of the sampled, digitized and reconstructed signal, for example the points of inflection, the curve maxima, or integrally by means of an optimum filter known from the time interpolation.
As an alternative or in addition to determining the pulse time of flight, a (fast) sampling is often also effected with regard to pulses or pulse sequences coded or modulated in terms of amplitude, phase, polarization, wavelength and/or frequency.
In the approach of temporally very precise sampling of the backscattered signal, the electrical signal generated by the detector is converted into a digital signal sequence by means of an analog-to-digital converter (ADC). Said digital signal is then usually processed further in real time. In a first step, the signal, often modulated as a pulse, is identified by specific digital filters and, finally, its position within the signal sequence is determined. By using a multiplicity of sampled pulse sequences, it is possible to identify a useful signal even under unfavorable circumstances, such that it is possible to cope with even relatively large distances or background scenarios that are noisy or beset by disturbances.
One of the simplest types of modulation is the identification of the individual pulses or pulse sequences by distance coding, as described e.g. in EP 1 832 897 B1. This is used for example for the purpose of re-identifiability. This re-identification is necessary if an ambiguity arises, which may be brought about by various situations during the time-of-flight measurement of pulses, for example if more than one pulse or a pulse group is situated between measuring apparatus and target object.
In fast analog-to-digital converters (ADC), the high sampling rate in conjunction with a high resolution of the signal amplitude (e.g. 1 GS/s, 14-bit) is achieved for example by the generation of a plurality of ADC conversion stages, for example by:                temporally interleaving (“interleave”) a plurality of slow ADC conversion stages,        quantizing the sampled signal amplitudes in stages (“pipeline”, “pipelining”), or        in combination multi-stage quantization of the signal samples of a plurality of ADC conversion stages.        
In the case of these architectures, architecture-typical errors arise despite careful internal corrections. Said errors vary over time and temperature.
In the case of interleaved ADCs, the errors arise in particular by virtue of the fact that the different ADC conversion stages do not have exactly identical properties with regard to offset, gain and timing. As a result, the typical errors are manifested in particular as:                skew (timing error between the sample instants of the different ADC conversion stages or ADCs);        gain (different gain factor between the internal ADC core components. The signal is usually amplified and/or buffered in the ADC);        offset (different DC levels of the internal outputs of the ADC conversion stages).        
In the case of pipelined ADCs, the typical errors are usually manifested as differential nonlinearity DNL and integral nonlinearity INL. DNL and INL are errors during the conversion of the analog signal values into digital (integral) values, for example brought about by the quantization in stages in a pipeline ADC with steps becoming finer and finer/resolution becoming higher and higher.
The INL error is essentially the partial sum of all the contributions of the DNL errors below the signal level to be converted and can attain a plurality of LSBs (“Least Significant Bits”). Therefore, even in the case of moderate fluctuations of the signal values, the INL error, in particular, has serious effects on the digitized signal waveform accuracy. The digitized signal waveform no longer corresponds to the original analog signal waveform. By means of internal corrections in the ADC component, these DNL and INL errors can be partly minimized, but not eliminated, and an external calibration, which may be realized by measuring and recording the residual error, is variable over time and for example highly temperature-dependent.
During the distance measurement, over distance periodic distance errors in the distance of the sampling/sample pattern arise as a result of the errors of the individual ADC conversion stages. The edges of a digital signal pulse are corrupted by the conversion errors in the excursion, as a result of which the position of the signal pulse can be shifted with respect to the time axis. Errors in the measurement distance can occur even in distance measuring systems having start and stop pulses or start and stop signal sequences. By way of example, this is the case if the start pulse has an amplitude in the medium modulation range, whereas the stop pulse has an amplitude in the lower amplitude range, wherein as a result of an INL-dictated shape distortion, for example, both pulses are deformed differently and the absolute distance is corrupted.